59 citations · 196 across the 20 of their papers we have counts for
20 papers
Large sample behavior of the least trimmed squares estimator
Yijun Zuo
The least trimmed squares (LTS) estimator is popular in location, regression, machine learning, and AI literature. Despite the empirical version of least trimmed squares (LTS) bein…
Asymptotic normality of the least sum of squares of trimmed residuals estimator
Yijun Zuo
To enhance the robustness of the classic least sum of squares (LS) of the residuals estimator, Zuo (2022) introduced the least sum of squares of trimmed (LST) residuals estimator.…
New algorithms for computing the least trimmed squares estimator
Yijun Zuo
Instead of minimizing the sum of all squared residuals as the classical least squares (LS) does, Rousseeuw (1984) proposed to minimize the sum of () smalles…
Least sum of squares of trimmed residuals regression
Yijun Zuo
In the famous least sum of trimmed squares (LTS) of residuals estimator (Rousseeuw (1984)), residuals are first squared and then trimmed. In this article, we first trim residuals -…
Non-asymptotic analysis and inference for an outlyingness induced winsorized mean
Yijun Zuo
Robust estimation of a mean vector, a topic regarded as obsolete in the traditional robust statistics community, has recently surged in machine learning literature in the last deca…
Non-asymptotic robustness analysis of regression depth median
Yijun Zuo
The maximum depth estimator (aka depth median) ($\bsβ^*_{RD}$) induced from regression depth (RD) of Rousseeuw and Hubert (1999) (RH99) is one of the most prevailing estimators in…